user
Name 5 methods of feature selection.
Response:
assistant
Five methods of feature selection are: 1) correlation-based, which looks for features that are highly correlated with the output; 2) wrapper methods, which uses algorithms to test various feature combinations; 3) embedding-based, which looks for lower-dimensional embeddings of the data; 4) recursive feature elimination, which eliminates features and tests the performance; and 5) filter methods, which uses statistical metrics and ranking to select features.